The Library
Probabilistic prediction of neurological disorders with a statistical assessment of neuroimaging data modalities
Tools
Tools
Tools
Filippone, M., Marquand, A. F., Blain, C. R. V., Williams, S. C. R., Mourão-Miranda, J. and Girolami, Mark (2012) Probabilistic prediction of neurological disorders with a statistical assessment of neuroimaging data modalities. The Annals of Applied Statistics, Volume 6 (Number 4). pp. 1883-1905. doi:10.1214/12-AOAS562 ISSN 1932-6157.
Research output not available from this repository.
Request-a-Copy directly from author or use local Library Get it For Me service.
Official URL: http://dx.doi.org/10.1214/12-AOAS562
Abstract
For many neurological disorders, prediction of disease state is an important clinical aim. Neuroimaging provides detailed information about brain structure and function from which such predictions may be statistically derived. A multinomial logit model with Gaussian process priors is proposed to: (i) predict disease state based on whole-brain neuroimaging data and (ii) analyze the relative informativeness of different image modalities and brain regions. Advanced Markov chain Monte Carlo methods are employed to perform posterior inference over the model. This paper reports a statistical assessment of multiple neuroimaging modalities applied to the discrimination of three Parkinsonian neurological disorders from one another and healthy controls, showing promising predictive performance of disease states when compared to nonprobabilistic classifiers based on multiple modalities. The statistical analysis also quantifies the relative importance of different neuroimaging measures and brain regions in discriminating between these diseases and suggests that for prediction there is little benefit in acquiring multiple neuroimaging sequences. Finally, the predictive capability of different brain regions is found to be in accordance with the regional pathology of the diseases as reported in the clinical literature.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
| Journal or Publication Title: | The Annals of Applied Statistics | ||||
| Publisher: | Institute of Mathematical Statistics | ||||
| ISSN: | 1932-6157 | ||||
| Official Date: | 27 December 2012 | ||||
| Dates: |
|
||||
| Volume: | Volume 6 | ||||
| Number: | Number 4 | ||||
| Page Range: | pp. 1883-1905 | ||||
| DOI: | 10.1214/12-AOAS562 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
